Triple
T72112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greek American |
E1443
|
entity |
| Predicate | communityInstitution |
P303
|
FINISHED |
| Object | Greek Orthodox parish |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Greek Orthodox parish | Statement: [Greek American, communityInstitution, Greek Orthodox parish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: communityInstitution Context triple: [Greek American, communityInstitution, Greek Orthodox parish]
-
A.
establishedInstitution
Indicates that an entity founded, created, or formally set up an institution or organization.
-
B.
workInstitution
Indicates that an entity is employed by or works at a particular institution.
-
C.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
D.
trainingInstitution
Indicates that one entity serves as the institution or organization where another entity receives training or education.
-
E.
hostsInstitution
Indicates that one entity serves as the hosting location or organizing body for an institution.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.